A new approach to determine the quality value of cotton fibres using multi-criteria decision making and genetic algorithm

Cotton is a natural fibre and possesses lot of variability in its properties. The overall quality of cotton fibre depends on strength, length, length uniformity, fineness, short fibre content etc. Therefore, determination of quality value of cotton fibre becomes a multi-criteria decision making (MCDM) problem. In this research, a new algorithm has been proposed and validated for determining the quality value of cotton fibre considering two yarn properties, namely yarn tenacity and unevenness. The algorithm works by amalgamating Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) and genetic algorithm (GA). The weights of the cotton fibre properties (decision criteria) have been optimized by the genetic algorithm whereas TOPSIS determined the quality value of cotton fibres. The proposed approach yields a cotton fibre quality index which shows high correlation with yarn tenacity and unevenness.

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